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endogenous-macrodynamics-in-algorithmic-recourse

Software and data underlying the publication: Endogenous Macrodynamics in Algorithmic Recourse

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contributors

Description

Code and research results for SaTML 2023 research paper. Originally released here: https://github.com/pat-alt/endogenous-macrodynamics-in-algorithmic-recourse.

The research results include:

Folders with images that went into a) the body of the paper or b) the online companion.Folders with results (.jls; .csv) for different experiments: a) synthetic data; b) real-world data; and, c) mitigation strategies for both categories of datasets (see paper for details on experiments). Results for all categories are further grouped by dataset.For each dataset, results include: a) "experiment.jls" files that can be loaded into a Julia session: the loaded Julia objects are structs that contain all settings characterizing a specific experiment. b) "output.csv" files that contain the final experimental outputs: estimated counterfactual evaluation metrics groups by model and counterfactual explainer.

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Keywords
Algorithmic Recourse
Counterfactual Explanations
Dynamic Systems
Explainable AI
Programming languages
License
  • MIT
</>Source code
Packages

Reference papers

Mentions

Contributors

AVD
Arie Van Deursen
CL
C.C.S. (Cynthia) Liem

Member of community

4TU